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Statistics in Kinesiology, Fifth Edition With Web Resource, offers students in kinesiology and exercise science programs a unique introduction to the statistics concepts and techniques relevant to their specific field of study. Drawing from examples across kinesiology, including exercise physiology, biomechanics, physical education, and physical therapy, this essential text provides students with a statistical skill set that will enable them to analyze quantitative data and find answers to questions they will encounter in their specific disciplines.
As in previous editions, emphasis is placed on methods commonly seen in kinesiology, such as correlation and bivariate regression, t tests, analysis of variance (ANOVA), and the interpretation of interactions in factorial analyses of variance. The fifth edition also incorporates fully updated content reflecting the changing face of kinesiology: Comparisons of observational versus experimental research and nonparametric versus parametric methods of analyzing categorical and ordinal data More detailed coverage on how to calculate central tendency when data have been transformed (e.
g. , log transformations) as well as multiple ways to interpret the correlation coefficient Expanded coverage of statistical graphs, including dot plots and spaghetti plots A discussion of the real meaning of p values and confidence intervals An introduction to frequentist approaches versus Bayesian methods In addition, a new web resource offers abridged presentations of complex statistical concepts and an interactive platform to practice problem solving.
Mini lectures, consisting of narrated slideshows, provide further explanations and may be quickly accessed through QR codes placed at the end of each chapter. Sample problems then provide an opportunity for students to put the concepts into practice. Statistical software tools commonly used in kinesiology applications—such as JASP and G*Power—are briefly introduced, encouraging students to apply their knowledge of statistical procedures to generate and interpret computer results with confidence and ease.
Annað
- Höfundar: Joseph P. Weir, William J. Vincent
- Útgáfa:5
- Útgáfudagur: 2020-03-04
- Engar takmarkanir á útprentun
- Engar takmarkanir afritun
- Format:ePub
- ISBN 13: 9781492595007
- Print ISBN: 9781492560715
- ISBN 10: 1492595004
Efnisyfirlit
- Title Page
- Copyright
- Dedication
- Contents
- Preface
- Acknowledgments
- List of Key Symbols
- Chapter 1. Measurement, Statistics, and Research
- What Is Measurement?
- Process of Measurement
- Variables and Constants
- Research Design and Statistical Analysis
- Statistical Inference
- Summary
- Chapter 2. Organizing and Displaying Data
- Organizing Data
- Displaying Data
- Summary
- Chapter 3. Percentiles
- Common Percentile Divisions
- Calculations Using Percentiles
- Summary
- Chapter 4. Measures of Central Tendency
- Mode
- Median
- Mean
- Relationships Among the Mode, Median, and Mean
- Logarithmic Transformations and the Geometric Mean
- Summary
- Chapter 5. Measures of Variability
- Range
- Interquartile Range
- Variance
- Standard Deviation
- Definition Method of Hand Calculations
- Calculating Standard Deviation for a Sample
- Coefficient of Variation
- Standard Deviation and Normal Distribution
- Graphical Depiction of the Standard Deviation
- Summary
- Chapter 6. The Normal Curve
- Z Scores
- Standard Scores
- Probability and Odds
- Calculating Skewness and Kurtosis
- Summary
- Chapter 7. Fundamentals of Statistical Inference
- Predicting Population Parameters Using Statistical Inference
- Estimating Sampling Error
- Frequentist Versus Bayesian Inference
- Levels of Confidence, Confidence Intervals, and Probability of Error
- An Example Using Statistical Inference
- Statistical Hypothesis Testing
- Type I and Type II Error
- Degrees of Freedom
- Living With Uncertainty
- Two- and One-Tailed Tests
- Applying Confidence Intervals
- Summary
- Chapter 8. Correlation and Bivariate Regression
- Correlation
- Calculating the Correlation Coefficient
- Bivariate Regression
- Homoscedasticity
- Summary
- Chapter 9. Multiple Correlation and Multiple Regression
- Multiple Correlation
- Partial Correlation
- Multiple Regression
- Summary
- Chapter 10. The t Test: Comparing Means From Two Sets of Data
- The t Tests
- Types of t Tests
- Magnitude of the Difference (Size of Effect)
- Determining Power and Sample Size
- The t Test for Proportions
- Summary
- Chapter 11. Simple Analysis of Variance: Comparing the Means Among Three or More Sets of Data
- Assumptions in ANOVA
- Sources of Variance
- Calculating F: The Definition Method
- Determining the Significance of F
- Post Hoc Tests
- Magnitude of the Treatment (Size of Effect)
- Summary
- Chapter 12. Analysis of Variance With Repeated Measures
- Assumptions in Repeated Measures ANOVA
- Calculating Repeated Measures ANOVA
- Correcting for Violations of the Assumption of Sphericity
- Post Hoc Tests
- Confidence Intervals and Effect Sizes
- Interpreting the Results
- Summary
- Chapter 13. Quantifying Reliability
- Intraclass Correlation Coefficient
- Standard Error of Measurement
- Summary
- Chapter 14. Factorial Analysis of Variance
- A Between–Between Example
- A Between–Within Example
- A Within–Within Example
- Summary
- Chapter 15. Analysis of Covariance
- Relationship Between ANOVA and Regression
- ANCOVA and Statistical Power
- Assumptions in ANCOVA
- The Pretest–Posttest Control Group Design
- Pairwise Comparisons
- Summary
- Chapter 16. Analysis of Nonparametric Data
- Chi-Square (Single Classification)
- Chi-Square (Two or More Classifications)
- Rank Order Correlation
- Mann-Whitney U Test
- Kruskal-Wallis ANOVA for Ranked Data
- Friedman’s Two-Way ANOVA by Ranks
- Summary
- Chapter 17. Clinical Measures of Association
- Relative Risk
- Odds Ratio
- Diagnostic Testing
- Summary
- Chapter 18. Advanced Statistical Procedures
- Multilevel Modeling
- Meta-Analysis
- Multiple Analysis of Variance
- Factor Analysis
- Discriminant Analysis
- Summary
- Appendix: Statistical Tables
- Glossary
- References
- Index
- About the Authors
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- Gerð : 208
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- Útgáfuár : 2012
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